We build on our previous work [1]} and use an information-theoretic measure
for the explainability of a particular predictor. In contrast to [1]},
we use this measure to directly steer the learning process for finding a good predictor map.
This leads naturally to a form of regularized empirical risk minimization [3]}, [4]}.
